Spatio-temporal modelling of informal settlement growth using a hybrid GIS and CA-Markov model - Daniels, Roger Hubert (School of Architecture, Planning and Geomatics, 2021)
The permanency and scale of informal settlement growth across the City of Cape Town cannot be promptly understood using the existing stock of human settlement planning tools and mapping techniques because the morphological patterns of informality are characterised by the complex commingling of multiple social and economic conditions, transactions, events and norms (Lejano and Del Bianco, 2018:203). In this research study, it is argued that a key focus area for future human settlement policy development should be fixed on establishing a greater understanding of the prevailing dispositions relating to how past and future morphological processes of informal settlements evolve. Towards acquiring this understanding, the research study develops a hybrid GIS and Cellular Automata Markov model, to simulate the future spatio-temporal growth of informal settlements in the City of Cape Town, Western Cape, South Africa from 2011 to 2051. To simulate growth, a raster-based model was operationalized using a Computer Simulation Package called TerrSet. The model inputs were determined by means of an online survey with various experts, and 13 model drivers were identified. These drivers were populated utilising, census data and other locational data for 2001 and 2011, sourced from Statistics South Africa and the City of Cape Town's Corporate GIS unit. This hybrid model was calibrated, by altering the size of the input grid cells and comparing the projected outputs with the actual 2018 land use dataset. To simulate growth, the calibrated hybrid model uses: Multi-Layer Perceptron Neural Network modelling components to determine a transitional probability map; Transitional probability matrix to determine the transitional rules for vacant-to-informal land use conversion; Markov Chain component to allocate the amount of future vacant-to-informal land use changes; and Cellular Automata to enable the spatial representation of vacant-to-informal grid cell changes. This model presents a novel approach for simulating informal settlement, and weighs in on the fragmented scientific debates in the field of (dynamic) hybrid spatial process modelling. Based on the simulation results, the main findings conclude that: drivers related to the location of informal dwelling structures, no access to piped water and high unemployment have the biggest effect on model accuracy; by 2031 the morphological patterns of informal settlement growth will begin to shift affecting additional lower to middle class communities located along the Cape Flats; and between 2031 and 2051 the location of informal settlements will move from the peri-urban regions into the urban regions of the Metropolitan.